Accès ouvert
2025
article
OpenAlex
Yong Bai, Xiangyu Guo, Keyin Liu, Bingjie Zheng et autres
Spatially resolved transcriptomics (SRT) for characterizing spatial cellular heterogeneities in tissue environments requires systematic analytical approaches to elucidate gene expression variations within their physiological context. Here, we introduce SpaSEG, an unsupervised deep learning model utilizing convolutional neural networks for multiple SRT analysis …
cn, dk
(code pays fourni par la source)
Accès ouvert
2022
preprint
OpenAlex
Yong Bai, Xiangyu Guo, Keyin Liu, Bingjie Zheng et autres
Abstract Spatially resolved transcriptomics (SRT) for characterizing cellular heterogeneities and activities requires systematic analysis approaches to decipher gene expression variations in physiological contexts. Here we develop SpaSEG, an unsupervised convolutional neural network-based model for multiple SRT analysis tasks by jointly learning the …
cn, dk
(code pays fourni par la source)
Accès ouvert
2022
article
OpenAlex
Ya ZENG, Li Wan, Qiuhong Luo, Mao CHEN
Traditional pipeline methods for task-oriented dialogue systems are designed individually and expensively. Existing memory augmented end-to-end methods directly map the inputs to outputs and achieve promising results. However, the most existing end-to-end solutions store the dialogue history and knowledge base (KB) information …
cn
(code pays fourni par la source)
2021
conference-paper
OpenAlex
Qiuhong Luo, Wan Li, Lichao Tian, Li Zhu
Recognition of insect pests in the wild plays a key role in crop protection. Large-scale pest recognition in natural scenes is extremely challenging due to significant intra-class variation and small inter-class variation within sub-categories. Existing works typically use state-of-the-art convolutional neural networks …
cn, gb
(code pays fourni par la source)